This project will substantially extend and improve the MOLPROBITY web service for analyzing, validating, and improving 3D macromolecular structures. It will enhance the basic capabilities, user-friendliness, generality, robustness, maintainability, and extensibility of MolPROBITY and its suite of supporting software in order to benefit both the many current users (11,500 working sessions this year) as well as the even broader community of biomedical researchers who now wish to employ it. MOLPROBITY has 2 unique features that enable these goals. 1 is all-atom contact analysis with explicit hydrogens, which shows steric contacts in unprecedented detail and has been proven capable of diagnosing and correcting most errors in experimental structural models. The second is the kinemage graphics concept implemented in MAGE and KING, emphasizing interactivity and clear perception of 3D relationships. Growing since 1992, this open-source, cross-platform software family supports structural biology, biochemistry, bioinformatics, educational, and even non-molecular uses. The new Protein Data Bank website and data-deposition makes use of these validation and graphics tools. Most structural genomics centers have adopted MOLPROBITY, but want it further tuned to the needs of their production pipelines. This project will enable development and documentation that is hard to justify in a pure research effort but is essential for long-term viability and growth as an open resource. Support will be added for structure comparisons, mmCIF files, and analysis of NMR ensembles and nucleic acids. Programs will be reorganized for modularity and better documented for re-use. MOLPROBITY'S web interface will be revised to give both intuitive simplicity for evaluation of deposited structures and also powerful flexibility for expert structural-biology clients solving new ones. Precalculated databases and links from other websites will allow quick access to structure quality evaluations and comparisons, serving an even broader set of biomedical researchers. Command-line and web service interfaces will serve new prediction and bioinformatics users analyzing thousands of files. User/collaborator feedback, advice from our computer science co-investigator, and our own experience in research use of the system will guide this software development process. For public health, MOLPROBITY can aid the success of computational design of new drugs, especially under time constraint (e.g. against SARS), since it helps users rapidly assess and improve the accuracy of experimentally determined models of drug targets. The work proposed here will lead to measurable improvement in overall accuracy of the 3D macromolecular database on which much of biomedical research depends. This is especially important for "hot" medically-relevant structures because time pressure currently compromises quality in many of these most health-relevant cases.